A Quantitative Model of the Considerations Determining Enlistment and Reenlistment Behavior

This project was designed to improve the understanding and modeling of the decisions, made each year by thousands of first-term soldiers, to reenlist in the Army or to leave for civilian jobs and school. A model of the reenlistment decision formulated from a decision-analytic perspective was develop...

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Hauptverfasser: Rakoff, Stuart H, Adelman, Leonard, Mandel, Jeffrey S
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Adelman, Leonard
Mandel, Jeffrey S
description This project was designed to improve the understanding and modeling of the decisions, made each year by thousands of first-term soldiers, to reenlist in the Army or to leave for civilian jobs and school. A model of the reenlistment decision formulated from a decision-analytic perspective was developed, based on an extensive review of the literature in the areas of military personnel, job satisfaction and job change, and decision theory, as well as from focus groups conducted with first-term soldiers at Fort Benning, Georgia. A multicomponent decision-modeling approach incorporating attitudinal, normative, and affective predictors of reenlistment intent was then developed, along with a set of instruments to capture data on these components. Consistent with previous findings for an enlistment task, the analysis of the pilot test data indicated that the three components predicted reenlistment intent in the following rank order: affect, attitudinal, and normative. The results also suggest that the Army has available tools for influencing these reenlistment decisions that are much more varied than the limited set of mainly economic factors that are now predominant in these programs. Specifically, the affective component dominated the economic variables in predicting reenlistment intent for this limited sample of soldiers, and may be an important reenlistment program and policy lever in the future. Keywords: Military personnel, Retention.
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A model of the reenlistment decision formulated from a decision-analytic perspective was developed, based on an extensive review of the literature in the areas of military personnel, job satisfaction and job change, and decision theory, as well as from focus groups conducted with first-term soldiers at Fort Benning, Georgia. A multicomponent decision-modeling approach incorporating attitudinal, normative, and affective predictors of reenlistment intent was then developed, along with a set of instruments to capture data on these components. Consistent with previous findings for an enlistment task, the analysis of the pilot test data indicated that the three components predicted reenlistment intent in the following rank order: affect, attitudinal, and normative. The results also suggest that the Army has available tools for influencing these reenlistment decisions that are much more varied than the limited set of mainly economic factors that are now predominant in these programs. Specifically, the affective component dominated the economic variables in predicting reenlistment intent for this limited sample of soldiers, and may be an important reenlistment program and policy lever in the future. 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Specifically, the affective component dominated the economic variables in predicting reenlistment intent for this limited sample of soldiers, and may be an important reenlistment program and policy lever in the future. 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Specifically, the affective component dominated the economic variables in predicting reenlistment intent for this limited sample of soldiers, and may be an important reenlistment program and policy lever in the future. Keywords: Military personnel, Retention.</abstract><oa>free_for_read</oa></addata></record>
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source DTIC Technical Reports
subjects ARMY PERSONNEL
BEHAVIOR
CIVILIAN PERSONNEL
DECISION MAKING
DECISION THEORY
ECONOMICS
EMOTIONS
GEORGIA
JOB SATISFACTION
JOBS
MILITARY PERSONNEL
PE65502A
Personnel Management and Labor Relations
PILOT STUDIES
PREDICTIONS
Psychology
RANK ORDER STATISTICS
RECRUITING
REENLISTMENT
TEST METHODS
VARIABLES
title A Quantitative Model of the Considerations Determining Enlistment and Reenlistment Behavior
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